Guest Seminar: Ratul Chowdhury Iowa State University Faculty January 10, 2023

Guest Seminar: Ratul Chowdhury Iowa State University Faculty January 10, 2023

When:
January 10, 2023 @ 3:30 pm – 5:30 pm
2023-01-10T15:30:00+05:30
2023-01-10T17:30:00+05:30
Where:
MSB 241
IIT Madras
Contact:
Abhijit P Deshpande
044-22574150

Title : Consequences of Single-Sequence Protein Structure Prediction
Date/Time : 10-01-2023 4:00PM
Venue : Chemical Engineering Auditorium MSB 241
Speaker: Prof Ratul Chowdhury

Biography of the Speaker :
Dr Ratul is an assistant professor of Chemical and Biological Engineering at Iowa State (research group areas – ChowdhuryLab (Structural Protein Biology and Engineering Lab – https://chowdhurylab.github.io/ – machine learning strategies, structure of a protein from its amino acid sequence. He received PhD in Chemical Engineering from Penn State University, in 2019 under the supervision of Prof. Costas D. Maranas. He was a structural computational structural biology postdoctoral Fellow in the lab of Peter Sorger in the Department of Systems Biology at Harvard Medical School.

Affiliation of the Speaker :
Assistant Professor Department of Chemical and Biological Engineering Iowa State University, Ames, Iowa. USA

Abstract :
Understanding protein structure involves being able to predict how a small change on an existing protein brings about large functional and structural changes. We are currently laying the groundwork for machine learning models of proteins and their interactions to (a) derive insight about their functions, (b) tune existing proteins for biochemical and pharmaceutical applications, and (c) point-of-care diagnostics. These models extract the ‘grammar’ of protein folding and they have been subsequently used to predict strategies for re-designing existing or de novo protein scaffolds for downstream applications. We focus on predicting protein structure from its amino acid sequence (with and without evolutionary data). Functional annotation maps these protein sequences onto high-dimensional spaces; nearby points are functionally related, where differe nt dimensions correspond to different functional properties. Looking forward, we will also focus on several applications spanning green chemistry, enzyme engineering, protein-pore-based separation devices, and biomimetic tissue design with immunotherapeutic use cases.